Blind signal separation using a combination of correlated and uncorrelated antenna elements

ABSTRACT

A communications device for separating source signals provided by M signal sources includes an antenna array comprising N antenna elements for receiving at least N different summations of the M source signals, with N and M being greater than 1. The N antenna elements include at least one antenna element for receiving at least one of the N different summations of the M source signals, and at least two correlated antenna elements for receiving at least two of the N different summations of the M source signals. The at least two correlated antenna elements are uncorrelated with the at least one antenna element. A receiver is connected to the antenna array. A blind signal separation processor is connected to the receiver for forming a mixing matrix comprising the at least N different summations of the M source signals, and for separating desired source signals from the mixing matrix. The mixing matrix has a rank equal up to at least N.

RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Ser.Nos. 60/612,546 filed Sep. 23, 2004; 60/612,435 filed Sep. 23, 2004;60/612,433 filed Sep. 23, 2004; 60/612,550 filed Sep. 23, 2004;60/612,632 filed Sep. 23, 2004; 60/612,548 filed Sep. 23, 2004;60/612,471 filed Sep. 23, 2004; 60/612,551 filed Sep. 23, 2004;60/612,469 filed Sep. 23, 2004; 60/612,547 filed Sep. 23, 2004;60/615,338 filed Oct. 1, 2004; 60/615,260 filed Oct. 1, 2004; 60/620,775filed Oct. 20, 2004; 60/620,776 filed Oct. 20, 2004; 60/620,862 filedOct. 20, 2004; 60/621,113 filed Oct. 22, 2004; and 60/639,223 filed Dec.23, 2004 the entire contents of which are incorporated herein byreference.

FIELD OF THE INVENTION

The present invention relates to the field of signal processing, andmore particularly, to separating desired source signals from a mixtureof source signals using blind signal separation (BSS) techniques.

BACKGROUND OF THE INVENTION

Blind source separation (BSS) involves recovering source signals from acomposite signal, wherein the composite signal includes a mixture of thesource signals. The separation is “blind” because it is often performedwith limited information about the signals, the sources of the signals,and the effects that the propagation channel has on the signals.

An example is the familiar “cocktail party” effect when a person at aparty is able to separate a single voice from a combination of all thevoices in the room. Blind source separation is particularly applicableto cellular and personal wireless communications devices, where manyfrequency bands have become cluttered with numerous radio frequencyemitters, often co-existing in the same spectrum. The problem ofco-channel emitters is expected to only worsen in years to come with thedevelopment of low power, unlicensed wireless technologies such asBluetooth and other personal area networks.

Three commonly used blind signal separation techniques are principalcomponent analysis (PCA), independent component analysis (ICA) andsingular value decomposition (SVD). PCA involves first and second momentstatistics of the source signals, and is used when the signal-to-noiseratios of the source signals are high. Otherwise, ICA is used whichinvolves PCA processing followed by third and fourth moment statisticsof the source signals. As an alternative, SVD may be used to separate asource signal from the mixture of source signals based upon theireigenvalues.

Regardless of the blind signal separation technique that is applied, aplurality of sensors is used to receive different mixtures of the sourcesignals from the various signal sources. Each sensor outputs a mixtureof the source signals, which is a unique sum of the source signals. Ingeneral, both the channel coefficients and the original source signalsare unknown to the receiver. The unique sums of signals are used topopulate a mixing matrix. The appropriate blind signal separationtechnique is then applied to the mixing matrix for separating desiredsource signals from the mixture of source signals.

As an example, U.S. Pat. No. 6,799,170 discloses the separation of anindependent source signal from a mixture of source signals using ICA. Aplurality of sensors receive the mixture of source signals, and aprocessor takes samples of the mixture of source signals over time andstores each sample as a data vector to create a data set. Each sensoroutputs a mixture of the source signals, which is a unique sum of thesource signals. An ICA module performs an independent component analysisof the data vectors to separate an independent source signal from othersignals in the mixture of source signals.

The sensors are spatially separated from one another, and the processorgenerates only one data vector for each respective sensor to create thedata set. The '170 patent also discloses that the number of sensors N isequal to or greater than the number of sources M, i.e., N≧M forpopulating the data set. A problem with such an implementation is thatas the number of sources M increases, then so does the number of sensorsN. Small portable communications devices have little available volumefor a large number of sensors N, and mounting the sensors on the outsideof the communications devices is a problem for the users.

U.S. Pat. No. 6,931,362 discloses another method for separating signalsusing blind signal separation. The disclosed blind signal separationtechnique forms a mixing matrix with hybrid matrix-pencil adaptive arrayweights that minimize the mean squared errors due to both interferenceemitters and Gaussian noise. The hybrid weights maximize the signal tointerference plus noise ratio. As with the '170 patent, the sensors arealso spatially separated from one another, and the number of sensors Nis equal to or greater than the number of sources M for populating themixing matrix. Moreover, each sensor provides a single input to themixing matrix resulting in a larger volume area for a portablecommunications device.

SUMMARY OF THE INVENTION

In view of the foregoing background, it is therefore an object of thepresent invention to provide a communications device comprising acompact antenna array for receiving a mixture of source signals for useby blind signal separation techniques so that desired source signals canbe separated therefrom.

This and other objects, features, and advantages in accordance with thepresent invention are provided by a communications device for separatingsource signals provided by M signal sources, with the communicationsdevice comprising an antenna array for receiving different summations ofthe M source signals. A receiver or receiver assembly is connected tothe antenna array, and a blind signal separation processor is connectedto the receiver for forming a mixing matrix. The mixing matrix comprisesthe different summations of the M source signals as received by theantenna array. The blind signal separation processor then separatesdesired source signals from the mixing matrix.

Instead of using spatially separated sensors to provide the differentsummations of the M source signals for the mixing matrix, a compactantenna array may be used instead. For portable communications devices,blind signal separation techniques may be used since the antenna arrayprovides more than one input to the mixing matrix while remainingcompact.

In particular, the antenna array may be a combination of correlated anduncorrelated antenna elements. For instance, the antenna array maycomprise N antenna elements for receiving at least N differentsummations of the M source signals, with N and M being greater than 1.The N antenna elements may comprise at least one antenna element forreceiving at least one of the N different summations of the M sourcesignals, and at least two correlated antenna elements for receiving atleast two of the N different summations of the M source signals. The atleast two correlated antenna elements may be uncorrelated with the atleast one antenna element. The blind signal separation processor mayform a mixing matrix comprising the at least N different summations ofthe M source signals. The mixing matrix may have a rank equal up to atleast N.

The number of antenna elements may equal the number of source signals,i.e., N=M. Alternatively, the number of antenna elements may be greaterthen the number of source signals, i.e., N>M. Another configuration iswhen the rank of the mixing matrix is equal to K, where K<N, and theblind signal separation processor separates K of the M source signalsfrom the mixing matrix.

The at least two correlated antenna elements may have differentpolarizations. The different polarizations may be orthogonal to oneanother. The at least two antenna elements that are correlated and havedifferent polarizations may comprise three antenna elements that arealso spatially correlated and have different polarizations so thattri-polarization is supported for receiving three different summationsof the M source signals.

The at least two correlated antenna elements may comprise at least twoactive antenna elements for forming a phased array. Alternatively, theat least two correlated antenna elements may comprise at least oneactive antenna element and at least one passive antenna element forforming a switched beam antenna.

A distinction may be made between patterns and beams when receiving thedifferent summations of the M source signals. In one case, the antennaarray may form at least N antenna beams for receiving the at least Ndifferent summations of the M source signals, with each antenna beamhaving 3 db points down from a maximum gain point thereof providing forsignal rejection in at least one direction of an approaching signal. Inanother case, the antenna array may form at least one antenna patternfor receiving at least one of the N different summations of the M sourcesignals, with the at least one antenna pattern having substantially no 3db points down from a maximum gain point thereof resulting in no signalrejection in any direction of an approaching signal.

Each summation of the M source signals is linear. The blind signalseparation processor may separate the desired source signals from themixing matrix based on at least one of principal component analysis(PCA), independent component analysis (ICA) and single valuedecomposition (SVD).

Another aspect of the present invention is directed to a method foroperating the communications device as defined above for separatingsource signals provided by the M signal sources. The method may comprisereceiving at the antenna array at least N different summations of the Msource signals. The N antenna elements may comprise at least one antennaelement for receiving at least one of the N different summations of theM source signals, and at least two correlated antenna elements forreceiving at least two of the N different summations of the M sourcesignals. The at least two correlated antenna elements may beuncorrelated with the at least one antenna element. The processing maycomprise forming a mixing matrix comprising the at least N differentsummations of the M source signals, and separating desired sourcesignals from the mixing matrix. The mixing matrix may have a rank equalup to at least N.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a typical operating scenario in which acommunications device receives desired and undesired signals from theirrespective signal sources in accordance with the present invention.

FIG. 2 is a more detailed block diagram of the communications deviceshown in FIG. 1.

FIG. 3 is a roadmap of the different approaches for creating the linearindependent summations of the source signals for the mixing matrix inaccordance with the present invention.

FIG. 4 is a block diagram of the antenna array configured as a switchedbeam antenna in accordance with the present invention.

FIG. 5 is a block diagram of the antenna array configured as a phasedarray in accordance with the present invention.

FIG. 6 is a block diagram of the antenna array configured with polarizedantenna elements in accordance with the present invention.

FIG. 7 is a 3-dimensional plot illustrating the use of tri-polarizationin accordance with the present invention.

FIG. 8 is a block diagram of a communications device with an antennaarray comprising correlated and uncorrelated antenna elements forproviding different summations of signals for blind signal separationprocessing in accordance with the present invention.

FIG. 9 is a block diagram of a communications device operating based onarray deflection for providing different summations of signals for blindsignal separation processing in accordance with the present invention.

FIG. 10 is block diagram of a switched beam antenna with an elevationcontroller for selectively changing an elevation of an antenna patternin accordance with the present invention.

FIG. 11 is an antenna plot illustrating an antenna pattern in theazimuth direction and then rotated in the elevation direction inresponse to the elevation controller illustrated in FIG. 9.

FIG. 12 is a block diagram of an antenna element with an RF choke formedin the ground plane for rotating the antenna pattern in the elevationdirection accordance with the present invention.

FIG. 13 is a block diagram of a communications device operating based onpath selection for providing different summations of signals for blindsignal separation processing in accordance with the present invention.

FIG. 14 is a block diagram of a communications device operating based onspreading codes for providing additional summations of signals for blindsignal separation processing in accordance with the present invention.

FIG. 15 is a block diagram of a communications device operating based onin-phase and quadrature signal components for providing additionalsummations of signals for blind signal separation processing inaccordance with the present invention.

FIG. 16 is a more detailed block diagram of an in-phase and quadraturemodule connected to an antenna element as shown in FIG. 15.

FIG. 17 is a block diagram of a MIMO system operating based on patterndiversity in accordance with the present invention.

FIG. 18 is a block diagram of a Fourier transform communications systemaddressing intersymbol interference (ISI) in accordance with the presentinvention.

FIG. 19 is a block diagram of a communications system in which atransmitter changes power levels for each layered space stream on a timeslotted basis in accordance with the present invention.

FIG. 20 is a block diagram of a communications system in whichundulating patterns are used to support multiple transmitterstransmitting to the same access point in accordance with the presentinvention.

FIG. 21 is a block diagram of a receiver optimizing processing and powerdrain in accordance with the present invention.

FIG. 22 is a block diagram of the receiver illustrated in FIG. 21coordinating its operation with a transmitter.

FIG. 23 is a plot of transmit pattern contours being undulated in atiming sequence known to a receiver in accordance with the presentinvention.

FIG. 24 is a time line in which a symbol period has 12 variations (i.e.,12 chips) while the parameter being varied is held constant for 4 chipsin accordance with the present invention.

FIG. 25 is a block diagram of a receiver for multiple spatialindependent channels in accordance with the present invention.

FIG. 26 is a block diagram of a receiver decoding chain in accordancewith the present invention.

FIGS. 27–30 are amplitude versus frequency plots respectivelycorresponding to nodes A, B, D and E in FIG. 26.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention will now be described more fully hereinafter withreference to the accompanying drawings, in which preferred embodimentsof the invention are shown. This invention may, however, be embodied inmany different forms and should not be construed as limited to theembodiments set forth herein. Rather, these embodiments are provided sothat this disclosure will be thorough and complete, and will fullyconvey the scope of the invention to those skilled in the art. Likenumbers refer to like elements throughout, and prime notation is used toindicate similar elements in alternative embodiments.

In communications networks there are source signals intended for aspecific communications device, and there are source signals intendedfor other communications devices operating within the same frequencyband. There are also sources of noise which produce signals that are notused for communications, but are received by the communications devicesas well.

To facilitate decoding of the source signals of interest, blind signalseparation is used to separate the signals received by a communicationsdevice. As noted above, the term “blind” refers to the fact that in anideal case the signals can be separated without any knowledge about thenature of the signals or the transformations that occur due tointeractions between the signals and the communication channel. Inpractical implementations, any knowledge that is available is oftenexploited. In this case, the signal separation is semi-blind.

Three commonly used techniques that fall under blind signal separationare principal component analysis (PCA), independent component analysis(ICA), and singular value decomposition (SVD). As long as the signalsare independent in some measurable characteristic, and if their signalsums are linearly independent from each other, one or more of theseblind signal separation techniques may be used to separate independentor desired source signals from a mixture of the source signals. Themeasurable characteristic is often some combination of the first,second, third or fourth moments of the signals.

PCA whitens the signals, uses first and second moments, and rotates thedata set based on correlation properties. If the signal-to-noise ratiosof the source signals are high, the signal separation process can stopwith PCA.

If the signal-to-noise ratios of the source signals are low, then ICAseparates the source signals based on statistical attributes involvingthe third and fourth moments of the source signals. Since the sourcesignals are Gaussian, their third and fourth moments are dependent onthe first and second moments. As an alternative to ICA and PCA, SVDseparates source signals from the mixture of source signals based upontheir eigenvalues.

A typical scenario is illustrated in FIG. 1, in which a plurality ofsignal sources 20 transmit source signals 22. The source signals 22 aretransmitted in a direction based upon generated antenna beams 24associated with each respective signal source 20. The plurality ofsignal sources 20 include a first signal source 20(1) through an Mthsignal source 20(M). Likewise, the respective source signals arereferenced 22(1)–22(M) and the corresponding antenna beams arereferenced 24(1)–24(M). More straightforward implementations are oftenutilized in communications networks in the form of omni-directionalantenna patterns or directional antenna patterns.

An antenna array 32 for the communications device 30 receives a linearcombination (mixture) of the source signals 22 from the signal sources20. The antenna array 32 comprises a plurality of antenna elements 34,with each antenna element providing at least one linear combination(mixture) of the source signals 22 from the signal sources 20. Theantenna elements 34 include a first antenna element 34(1) through an Nthantenna element 34(N).

The received source signals 22(1)–22(M) are initially formed into amixing matrix 36. The communications device 30 uses blind signalseparation techniques to determine a separation matrix 38 for separatingthe source signals in the mixing matrix. The separated signals arerepresented by reference 39

The communications device 30 jointly extracts the mixture of sourcesignals received by the antenna array 32 by sampling an aggregate orcomposite of the received source signals without knowledge of theircharacteristics. The output of each antenna element 34 is modeled as asummation of the source signals 22 after having been convolved with theimpulse response of the channel, i.e., the propagation path between theoutput of a signal source 20 and the output of an antenna element 34plus additive Gaussian noise.

The communications device 30 for separating source signals provided bythe M signal sources 20(1)–20(M) will now be discussed in greater detailwith reference to FIG. 2. An antenna array 34 includes N antennaelements 34(1)–34(N) for receiving up to at least N different summationsof the M source signals, with N and M being greater than 1. The antennaarray 32 is not limited to any particular configuration. The antennaarray 32 may include one or more antenna elements 34. The antennaelements 34 may be configured so that the antenna array 32 forms aphased array or switched beam antenna, for example, as will be discussedin greater below.

A transceiver 40 is connected downstream to the antenna array 32 forreceiving up to the at least N different summations of the M sourcesignals 22. A processor 42 is downstream to the transceiver 40. Eventhough the processor 42 is illustrated separate form the transceiver 40,the processor may also be included within the transceiver. The differentsummations of the M source signals 22 received by the transceiver 40 areused to populate the mixing matrix 36. The mixing matrix 36 is thenprocessed by one or more blind signal separation processing modules 44,46 and 48 within the processor 42.

The blind signal separation processing modules include a PCA module 44,an ICA module 46 and an SVD module 48. These modules 44, 46 and 48 maybe configured as part of a blind signal separation processor 49. The PCAmodule 44 operates based on the first and second moments of thedifferent summations of the received source signals, whereas the ICAmodule 46 operates based on the third and fourth moments of the samesignals. The SVD module 48 performs signal separation based on theeigenvalues of the different summations of the received source signals.

The correlation processing initially performed by the PCA module 44determines an initial separation matrix 38(1) for the differentsummations of the source signals, and the ICA module 46 then determinesan enhanced separation matrix 38(2) for separating the source signals inthe mixing matrix 36. If the signals are separated by the SVD module 48,a separation matrix 38(3) is also determined for separating thedifferent summations of the received source signals in the mixing matrix36.

From each respective separation matrix 38(1)–38(3), the separatedsignals are represented by reference number 39. The separated signals 39then they undergo signal analysis by a signal analysis module 50 todetermine which signals are of interest and which signals areinterferers. An application dependent processing module 52 processes thesignals output from the signal analysis module 50.

The decision on which signals are of interest may not always involve thefinal signal to be decoded. For instance, the application may call foridentifying interferers and subtracting them from the differentsummations of the received source signals, and then feeding the reducedsignal to a waveform decoder. In this case, the signals of interest arethe ones that ultimately end up being rejected.

The information fed to the PCA module 44 is a unique sum of signalsx_(j). It is assumed that N linear mixtures x₁, . . . , x_(N) of Mindependent components are observed:

x₁(t) = a₁₁s₁(t) + …  a_(1k)s_(k)(t) + …  a_(1M)s_(M)(t) ⋮x_(j)(t) = a_(j1)s₁(t) + …  a_(jk)s_(k)(t) + …  a_(jM)s_(M)(t) ⋮x_(N)(t) = a_(N1)s₁(t) + …  a_(Nk)s_(k)(t) + …  a_(NM)s_(M)(t)

In general, both the channel coefficients a_(jk) and the originalsignals s_(k) are unknown to the transceiver 40. In matrix notation theabove set of equations may be compactly written as x=As, where A is themixing matrix. The statistical model x=As is also known as the ICAmodel. Traditional techniques try to find the inverse of the channel:s=A⁻¹x.

The ICA module 46 determines a separation matrix W, and y=W(As)=Wx. Thevector y is a subset of s in unknown order with scaling changes. If allthe signals are not separable, the more general form would bey=W(As)+Wn=Wx+Wn, where the additional n term is the residual noise dueto the unidentifiable sources.

The ICA model is a generative model, which means that it describes howthe observed data is generated by a process of mixing the componentss_(k). The independent components are latent variables, meaning thatthey cannot be directly observed. Also, the mixing matrix A is assumedto be unknown. All that is observed is the random vector x, and A and sare to be estimated based upon x.

The starting point of ICA is the assumption that the components s_(k)are statistically independent. Moreover, it is assumed that theindependent components s_(k) at most have one with a Gaussiandistribution. The one signal with a Gaussian distribution limitation isdue to the fact that the third moment of a Gaussian signal is 0, and theforth moment is indistinguishable amongst Gaussian signals.

For simplicity, the unknown mixing matrix A is assumed to be square.Thus, the number of independent components is equal to the number ofobserved mixtures. However, this assumption can be relaxed at times. Aslong as the signals s_(k) are statistically independent in somemeasurable characteristic, the separation matrix W can be determined.

The rank of the mixing matrix A determines how many signals can actuallybe separated. For example, a mixing matrix having a rank of 4 means that4 source signals can be separated. Ideally, the rank of the mixingmatrix A should at least be equal to the number of signal sources M. Thelarger the rank, the more signals that can be separated. As the numberof sources M increases, then so does the required number of antennaelements N. The '170 and '362 patents discussed in the backgroundsection both disclose that the number of antenna elements N are equal toor greater than the number of signal sources M, i.e., N≧M., otherwise atechnique other than blind signal separation is to be used to separatethe signals.

An industry standard for creating the linearly independent sums ofsignals is to use N uncorrelated sensors, i.e., the sensors are spacedat least a wavelength apart from one another. The wavelength is basedupon the operating frequency of the communications device 30. The Nsensors are uncorrelated in space, but correlated in polarization and inangle. The N uncorrelated sensors provide N sums of linearly independentsignals, where each sensor provides a single entry into the mixingmatrix A.

A roadmap or outline of the different approaches for creating the linearindependent summations of the source signals for the mixing matrix Awill initially be discussed with reference to FIG. 3. After a briefintroduction, each approach will be discussed in greater detail below.

The first section of the roadmap addresses antenna configurations. Block100 represents uncorrelated sensors, wherein each sensor provides asingle input to the mixing matrix A. Block 102 represents a correlatedantenna array, wherein the array provides multiple inputs to populatethe mixing matrix A. Block 104 also represents an antenna array, whereina portion of the antenna elements is correlated and the antenna elementshave different polarizations for populating the mixing matrix A.Different combinations of the sensors and antenna arrays addressed byBlocks 100, 102 and 104 may be combined in Block 106 to further populatethe mixing matrix in Block 116.

The second section of the roadmap addresses enhancements to the antennaconfigurations provided in the first section. The enhancements are madeso that additional or replacement summations of the source signals arecollected to further populate the mixing matrix A. Block 108 involvesarray deflection in which the elevation of the antenna patterns ischanged for receiving additional summations of the source signals.Anyone of the combinations in Block 106 may be used in the arraydeflection Block 108.

In Block 110, path selection is performed so that all of the summationsof the source signals used to populate the mixing matrix A arecorrelated (1^(st) and 2^(nd) moments) and/or statistically (3^(rd) and4^(th) moments) independent. In other words, the incident signals areselectively chosen for receiving new summations of the source signals toreplace the summations that are not correlated and/or statisticallyindependent. Block 110 may be fed by anyone of the combinations in Block106 and 108. Blocks 108 and 110 may be fed directly to the mixing matrixBlock 116.

The third section of the roadmap addresses signal splitting for furtherpopulating the mixing matrix in Block 116. For example, Block 112 splitsthe different summation signals using spreading codes. If a summationsignal has k spreading codes, then that particular summation signal maybe processed to provide k summation signals associated therewith. Thespreading codes may be applied in combination with the outputs of Blocks106, 108 and 110. Block 114 splits the different summation signals intoin-phase (I) and quadrature (Q) components to further populate themixing matrix. The I and Q components thus act as a multiplier of 2 forthe missing matrix, and may be applied in combination with the outputsof Blocks 106, 108, 110 and 112.

The final section of the roadmap is the mixing matrix A formed in Block116. As illustrated in the roadmap, the mixing matrix A may be populatedwith the different summations of the source signals based on anyone ofthe above described blocks. An advantage of the antenna arrayconfigurations in the first section is that compact antenna arrays maybe formed for populating the mixing matrix A. An advantage of theantenna array configurations in the second and third sections is that Nantenna elements, where N is less than the number M of source signals,can be used to populate the mixing matrix with M or more summations ofthe source signals.

In view of the antenna configurations discussed in the roadmap, anantenna array comprising N correlated antenna elements for receiving atleast N different summations of the M source signals, with N and M beinggreater than 1, will be discussed. In one embodiment, the antenna arrayis a switched beam antenna 140 as illustrated in FIG. 4.

The switched beam antenna array 140 generates a plurality of antennapatterns, including directional antenna patterns and an omni-directionalantenna pattern. The switched beam antenna 140 includes an activeantenna element 142 and a pair of passive antenna elements 144. Theactual number of active and passive antenna elements 142, 144 variesdepending on the intended application. Reference is directed to U.S.patent application Ser. No. 11/065,752 for a more detailed discussion onthe switched beam antenna array. This patent application is assigned tothe current assignee of the present invention, the contents of which areincorporated herein by reference in its entirety.

Each passive antenna element 144 includes an upper half 144 a and alower half 144 b. The upper halves 144 a of the passive antenna elements144 are connected to a ground plane 146 through reactive loads 148. Thereactive loads 148 are a variable reactance, which is changeable incapacitance to inductance by using varactors, transmission lines orswitching. By varying the reactive loads 148, the radiation patterns canbe changed. Since there are two passive antenna elements 144, fourdifferent antenna patterns can be formed.

Three of the antenna patterns can be used to receive a unique sum ofsignals x_(j). The fourth pattern is a linear combination of the otherthree, so it is not usable as an entry in the mixing matrix A.Consequently, with three antenna elements being utilized, three uniquesum of signals x_(j) are input to the mixing matrix A. An advantage ofthe switched beam antenna is that by using 3 elements 142 and 144, amixing matrix of rank 3 can be supported.

In another embodiment, the antenna array comprises N correlated activeantenna elements so that the antenna array forms a phased array 160, asillustrated in FIG. 5. The phased array 160 comprises a plurality ofactive antenna elements 162, and a plurality of weight controlcomponents 164 coupled to the active antenna elements. The weightcontrol components 164 adjust the amplitude and/or phase of the receivedsignals to form a composite beam.

A splitter/combiner 166 and a controller 168 are connected to the weightcontrol components 164. Reference is directed to U.S. Pat. No. 6,473,036for a more detailed discussion on the active array 160. This patent isassigned to the current assignee of the present invention, the contentsof which are incorporated herein by reference in its entirety.

The number of active elements 162 supports a mixing matrix A having thesame rank. Even though the number of sources M is equal to the number ofactive elements N, i.e., M=N, the active array 100 is compact since theactive elements 162 are correlated in space and polarization, ascompared to the traditional approach of using uncorrelated antennaelements that are spaced more than a wavelength apart.

In other embodiments, the rank of the mixing matrix may be K, where K<N,so that the blind signal separation processor 49 separates K of the Msource signals from the mixing matrix. As will be discussed in greaterdetail below, N may also be greater than M.

In both the switched beam antenna 140 and the phased array 160, thedistance between their respective antenna elements 142, 144 and 162 isset to allow a favorable back to front ratio. This is because theclassical use of these antenna arrays is to reject unwanted signals(i.e., back approaching) and intensify wanted signals (i.e., frontapproaching).

However, for the purpose of building mixing matrices, the goal is createdifferent sums of signals. The signals of interest can actually alwaysbe lower than the interferers in this application and still beseparated. Because of this significant difference in purpose, thedistances between antenna elements need not be of a specific separation.

The antenna elements could be further or closer together, generatepatterns with classically ‘bad’ front to back ratios, and still be quitesuitable for mixing matrix usage. If fact, such patterns will often besuperior in the blind signal source separation application. The reasonbeing that the use of good front to back ratios requires tracking of thesignal directions in order to keep the front pointed at the desiredsignal and/or the back at interferers. By using patterns which havedifferences in various directions, but still significant gains, no suchtracking of the signals is required.

An antenna beam may be defined as having 3 db points down from a maximumgain point thereof providing for signal rejection in at least onedirection of signal approach. Similarly, an antenna pattern may bedefined as having substantially no 3 dB points down from a maximum gainpoint thereof and having no signal rejection in any direction of signalapproach.

In many applications this deviation from specific distances betweenelements can greatly reduce the size of the overall antenna array. Inother applications it might actually be desirable to increase thedistance between elements to alleviate the tracking problem, but gainsome degree of additional signal decorrelation.

In another embodiment, the antenna array 180 comprises N antennaelements for receiving at least N different summations of the M sourcesignals, as illustrated in FIG. 6. At least two of the N antennaelements 182 a, 182 b are correlated and have different polarizationsfor receiving at least two of the N different summations of the M sourcesignals, with N and M being greater than 1.

The other antenna elements 184 a, 184 b in the array 180 may becorrelated or uncorrelated with respect to antenna elements 182 a, 182b. Even though another pair of polarized antenna elements 184 a, 184 bare illustrated, these elements may instead have the same polarization.Moreover, these elements may also be uncorrelated with one another.

The different polarizations for antenna elements 182 a, 182 b may beorthogonal to one another. In another configuration, the antennaelements 182 a, 182 b include a third element 182 c so thattri-polarization is supported for receiving 3 different summations ofthe M source signals.

The following discussion supports the use of polarization for populatingthe mixing matrix A. The three differently polarized antenna elements182 a, 182 b, 182 c receive three linear and independent signals sums.The definitions and relationships of the x, y and z axis as illustratedin FIG. 7 will be used. For example, the following relationships exist:

x = S  cos (θ)sin (ϕ) y = S  sin (θ)sin (ϕ) z = S  cos (ϕ)

Simplifying assumptions are that the signals have linear polarization,the signals are linearly independent, and there are three linear antennaelements each on an orthogonal axis. For example, antenna element 182 ais on the x axis, antenna element 182 b is on the y axis, and antennaelement 182 c is on the z axis.

By positioning the three linear antenna elements 182 a, 182 b, 182 ceach on an orthogonal axis, the mathematics is simplified. In an actualdeployment, the antenna elements 182 a, 182 b, 182 c need not bestrictly orthogonal, nor do they need to meet at a common point. Theremoval of this assumption will not invalidate the general conclusion,but rather change the cases under which rank deficiency occurs.

The following definitions are applied, wherein numeric subscripts referto associations with signals 1, 2, 3:

-   S₁,S₂,S₃ Signals incident to the antenna elements;-   θ₁,θ₂,θ₃: The X, Y plane E field angle of the signal;-   φ₁,φ₂,φ₃: The Z axis E field angle of the signal; and-   X_(x),X_(y),X_(z): Dot product of the sum of signals incident to an    antenna element.

Therefore, the vector components are:

x y z Element ‘x’: 1 0 0 Element ‘y’: 0 1 0 Element ‘z’: 0 0 1 S₁Coefficient: cos(θ₁)sin(φ₁) sin(θ₁)sin(φ₁) cos(φ₁) S₂ Coefficient:cos(θ₂)sin(φ₂) sin(θ₂)sin(φ₂) cos(φ₂) S₃ Coefficient: cos(θ₃)sin(φ₃)sin(θ₃)sin(φ₃) cos(φ₃)

Taking the dot product of each antenna element and signal,(X·Y=x₁x₂+y₁y₂+z₁z₂) determines the relative E field component summed inthe element. These values are used to create the mixing matrix:

$\begin{bmatrix}X_{x} \\X_{y} \\X_{z}\end{bmatrix} = {\begin{bmatrix}{{\cos\left( \theta_{1} \right)}{\sin\left( \phi_{1} \right)}} & {{\cos\left( \theta_{2} \right)}{\sin\left( \phi_{2} \right)}} & {{\cos\left( \theta_{3} \right)}{\sin\left( \phi_{3} \right.}} \\{{\sin\left( \theta_{1} \right)}{\sin\left( \phi_{1} \right)}} & {{\sin\left( \theta_{2} \right)}{\sin\left( \phi_{2} \right)}} & {{\sin\left( \theta_{3} \right)}{\sin\left( \phi_{3} \right)}} \\{\cos\left( \phi_{1} \right)} & {\cos\left( \phi_{2} \right)} & {\cos\left( \phi_{3} \right)}\end{bmatrix}\begin{bmatrix}S_{1} \\S_{2} \\S_{3}\end{bmatrix}}$where:

$\begin{matrix}{{\det\begin{bmatrix}X_{x} \\X_{y} \\X_{z}\end{bmatrix}} = {{{\cos\left( \theta_{1} \right)}{\sin\left( \phi_{1} \right)}{\sin\left( \theta_{2} \right)}{\sin\left( \phi_{2} \right)}{\cos\left( \phi_{3} \right)}} +}} \\{{{\cos\left( \theta_{2} \right)}{\sin\left( \phi_{2} \right)}{\sin\left( \theta_{3} \right)}{\sin\left( \phi_{3} \right)}{\cos\left( \phi_{1} \right)}} +} \\{{{\cos\left( \theta_{3} \right)}{\sin\left( \phi_{3} \right)}{\sin\left( \theta_{1} \right)}{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}} -} \\{{{\cos\left( \phi_{1} \right)}{\sin\left( \theta_{2} \right)}{\sin\left( \phi_{2} \right)}{\cos\left( \theta_{3} \right)}{\sin\left( \phi_{3} \right)}} -} \\{{{\cos\left( \phi_{2} \right)}{\sin\left( \theta_{3} \right)}{\sin\left( \phi_{3} \right)}{\cos\left( \theta_{1} \right)}{\sin\left( \phi_{1} \right)}} -} \\{{\cos\left( \phi_{3} \right)}{\sin\left( \theta_{1} \right)}{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{\sin\left( \phi_{2} \right)}} \\{= {{{\cos\left( \theta_{1} \right)}{\sin\left( \theta_{2} \right)}{\sin\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\cos\left( \phi_{3} \right)}} +}} \\{{{\cos\left( \theta_{2} \right)}{\sin\left( \theta_{3} \right)}{\cos\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} +} \\{{{\sin\left( \theta_{1} \right)}{\cos\left( \theta_{3} \right)}{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} -} \\{{{\sin\left( \theta_{2} \right)}{\cos\left( \theta_{3} \right)}{\cos\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} -} \\{{{\cos\left( \theta_{1} \right)}{\sin\left( \theta_{3} \right)}{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} -} \\{{\sin\left( \theta_{1} \right)}{\cos\left( \theta_{2} \right)}{\sin\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\cos\left( \phi_{3} \right)}} \\{= {{{\cos\left( \theta_{1} \right)}{\sin\left( \theta_{2} \right)}{\sin\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\cos\left( \phi_{3} \right)}} -}} \\{{{\sin\left( \theta_{1} \right)}{\cos\left( \theta_{2} \right)}{\sin\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} +} \\{{{\cos\left( \theta_{2} \right)}{\sin\left( \theta_{3} \right)}{\cos\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} -} \\{{{\sin\left( \theta_{2} \right)}{\cos\left( \theta_{3} \right)}{\cos\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} +} \\{{{\sin\left( \theta_{1} \right)}{\cos\left( \theta_{3} \right)}{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} -} \\{{\cos\left( \theta_{1} \right)}{\sin\left( \theta_{3} \right)}{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}} \\{= {{{\sin\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{{\cos\left( \phi_{3} \right)}\left\lbrack {{{\cos\left( \theta_{1} \right)}{\sin\left( \theta_{2} \right)}} - {{\sin\left( \theta_{1} \right)}{\cos\left( \theta_{2} \right)}}} \right\rbrack}} +}} \\{{{\cos\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{{\sin\left( \phi_{3} \right)}\left\lbrack {{{\cos\left( \theta_{2} \right)}{\sin\left( \theta_{3} \right)}} - {{\sin\left( \theta_{2} \right)}{\cos\left( \theta_{3} \right)}}} \right\rbrack}} +} \\{{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{{\sin\left( \phi_{3} \right)}\left\lbrack {{{\sin\left( \theta_{1} \right)}{\cos\left( \theta_{3} \right)}} - {{\cos\left( \theta_{1} \right)}{\sin\left( \theta_{3} \right)}}} \right\rbrack}} \\{= {{{\sin\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\cos\left( \phi_{3} \right)}{\sin\left( {\theta_{2} - \theta_{1}} \right)}} +}} \\{{{\cos\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}{\sin\left( {\theta_{3} - \theta_{2}} \right)}} +} \\{{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{\sin\left( \phi_{3} \right)}{\sin\left( {\theta_{1} - \theta_{3}} \right)}}\end{matrix}$

Rank deficiency situations will now be discussed. When the determinantis equal to 0, the mixing matrix is rank deficient. This occurs in thefollowing cases:1) θ₁=θ₂=θ₃

The ‘x’ and ‘y’ elements are receiving the same contribution from allthree signals.

$\begin{matrix}\begin{matrix}\phi_{1} & \phi_{2} & \phi_{3} \\0 & 0 & 0 \\0 & 0 & {90{^\circ}} \\0 & {90{^\circ}} & 0 \\{90{^\circ}} & 0 & 0 \\{90{^\circ}} & {90{^\circ}} & {90{^\circ}}\end{matrix} & \left. 2 \right)\end{matrix}$

Add 180 degrees to any combination of table entries for another rankdeficient instance. These are occurrences when the signals are not beingindependently summed by a sufficient combination of antenna elements.

3) All the individual sums do not equal 0 per 1 or 2, but:

sin (ϕ₁)sin (ϕ₂)cos (ϕ₃)sin (θ₂ − θ₁) + cos (ϕ₁)sin (ϕ₂)sin (ϕ₃)sin (θ₃ − θ₂) + sin (ϕ₁)cos (ϕ₂)sin (ϕ₃)sin (θ₁ − θ₃) = 0

This implies a small solid angle of separation between the signals, nearequal polarization of the signals, signals aligned but coming fromopposite sides of the array, or some other very unlikely happenstance ofsignal incidence resulting in the same energy level to both elements.

As discussed above, the first section of the roadmap addresses antennaconfigurations. The above described antenna configurations, includinguncorrelated sensors, may be combined in a variety of differentconfigurations for providing the summed signals of the M source signalsto the mixing matrix.

Referring now to FIG. 8, a communications device 200 for separatingsource signals provided by M signal sources will be discussed. Theantenna array 202 comprises N antenna elements for receiving at least Ndifferent summations of the M source signals, with N and M being greaterthan 1.

The N antenna elements comprises at least one antenna element 204 forreceiving at least one of the N different summations of the M sourcesignals, and at least two correlated antenna elements 206 for receivingat least two of the N different summations of the M source signals. Thetwo correlated antenna elements 206 are uncorrelated with the antennaelement 204. The antenna array may include additional antenna elementsin various combinations in which the elements are correlated,uncorrelated and polarized.

A receiver 210 is connected to the antenna array 202 for receiving theat least N different summations of the M source signals. A blind signalseparation processor 212 is connected to the receiver for forming amixing matrix 214 comprising the at least N different summations of theM source signals. The mixing matrix has a rank equal up to at least N,and the blind signal separation processor 212 separates desired sourcesignals 216 from the mixing matrix A.

The second section of the roadmap addresses enhancements to the antennaconfigurations provided in the first section. The enhancements are madeso that additional or replacements summations of the source signals arecollected to further populate the mixing matrix A.

One enhancement involves array deflection for receiving additional sumsof signals for use by the mixing matrix A without having to addadditional antenna elements. Array deflection involves controllingantenna patterns in the azimuth and/or elevation direction.

A communications device 240 for separating source signals provided by Msignal sources using array deflection will now be discussed in referenceto FIG. 9. The antenna array 242 comprises N antenna elements 244 forgenerating N initial antenna patterns for receiving N differentsummations of the M source signals. The antenna array 242 also comprisesan elevation controller 246 for selectively changing an elevation of atleast one of the N initial antenna patterns for generating at least oneadditional antenna pattern so that at least one additional differentsummation of the M source signals is received thereby.

A receiver 248 is connected to the antenna array 242 and receives the Ndifferent summations of the M source signals using the N initial antennapatterns, and also receives the at least one additional differentsummation of the M source signals using the at least one additionalantenna pattern.

A blind signal separation processor 250 is connected to the receiver 248for forming a mixing matrix 252 comprising the N different summations ofthe M source signals and the at least one additional different summationof the M source signals. The mixing matrix has a rank equal to N plusthe number of additional different summations of the M source signalsreceived using the additional antenna patterns. The processor 250separates desired signals 254 from the mixing matrix.

In general, any antenna array means which provides signal sums suitablefor increasing the rank of the mixing matrix can be utilized with adeflection mechanism. The deflection will generate two distinct andmixing matrix usable signal sums for each of the antenna array means.There is therefore a 2 times multiplier effect by utilization of thistechnique.

If the array deflection is segmented into K distinct areas associatedwith an antenna, each of the K areas can provide for 2 independentdeflection areas and entries into the mixing matrix. For instance, ifthe antenna array can provide N summations by itself and there are Kdistinct deflection areas, the number of signal sums in the mixingmatrix may be 2*K*N.

For illustration purposes, reference is directed to FIG. 10 in which theswitched beam antenna 100′ shown in FIG. 4 has been modified so that theantenna patterns may be tilted up or down in elevation. In particular,each upper half 104 a′ of the passive antenna elements 104′ is connectedto the ground plane 106′ through a reactive load 108′. Each lower half104 b′ of the passive antenna elements 104′ is also connected to theground plane 106′ through a reactive load 108′. A reactance on thepassive antenna elements 104′ has the effect of lengthening orshortening the passive antenna element. Inductive loads lengthen andcapacitive loads shorten the electrical length of the passive antennaelements 104′.

An antenna beam is tilted up and down in elevation in accordance withthe ratios of the reactive loads 108′ of the upper halves 104 a′ and thereactive loads 118′ of the lower halves 104 b′. By adjusting the ratio,the antenna pattern can point up 97 or down 99, as illustrated in FIG.11. At least one additional rank is added to the mixing matrix A when anelevation angle of an antenna pattern is adjusted to receive a mixedsignal. Using the array deflection, more signals can be received for themixing matrix A without having to increase the number of antennaelements N.

This particular implementation has 2 distinct deflection areasindividually controlled by the reactances 118′. The pattern generationcapability of the array is 3 independent patterns, therefore the numberof signal sums that can be used to create the mixing matrix is 12(2*2*3).

Reference is directed to the above reference U.S. patent applicationSer. No. 11/065,752, which discloses how to adjust antenna beams inelevation in greater detail. The array deflection technique may beapplied to any of the above discussed antenna array embodiments, or anyother antenna array which is sensitive to ground plane interactions.

Another embodiment of the elevation controller is based upon acontrollable RF choke 270 coupled to the ground plane 272 of an antennaelement 274, as illustrated in FIG. 12. The antenna pattern associatedwith the antenna element 274 is moved in elevation by controlling the RFchoke 270, as readily appreciated by those skilled in the art.

A communications device 300 for separating source signals provided by Msignal sources based on path selection will be discussed in reference toFIG. 13. This is another enhancement to the antenna configurationsprovided in the first sections of the roadmap, as well as an enhancementto the array deflection discussed above. The communications device 300comprises an antenna array 302 comprising N elements 304 for forming atleast N antenna beams for receiving at least N different summations ofthe M source signals, with N and M being greater than 2.

A controller 306 is connected to the antenna array for selectivelyforming the at least N antenna beams. A receiver assembly 308 isconnected to the antenna array 302 for receiving the at least Ndifferent summations of the M source signals. A blind signal separationprocessor 310 is connected to the receiver assembly 308 for forming amixing matrix 312 comprising up to the at least N different summationsof the M source signals.

The blind signal separation processor 310 also determines if thedifferent summations of the M source signals are correlated orstatistically independent, and if not, then cooperating with thecontroller 306 for forming different beams for receiving new differentsummations of the M source signals to replace the different summationsof the M source signals that are not correlated or statisticallyindependent in the mixing matrix 312. The desired source signals 314 arethen separated from the mixing matrix 312.

A rake receiver is a radio receiver designed to counter the effects ofmultipath fading. It does this by using several independent receiverseach delayed slightly in order to tune in to the individual multipathcomponents. It can be used by most types of radio access networks. Ithas been found to be especially beneficial for spreading code types ofmodulation. Its ability to select specific incident signal paths make itsuitable as a means to change the paths fed to the blind signalseparation processing.

Selectively forming the N antenna beams as discussed above may beapplied to all radio access networks, as readily understood by thoseskilled in the art. For CDMA systems, the receiver assembly 308comprises N rake receivers 316. Each rake receiver 316 comprises kfingers for selecting k different multipath components for each one ofthe N different summations of the M source signals received by therespective antenna element connected thereto. In this configuration, theblind signal separation processor 310 is connected to the N rakereceivers 316 for forming the mixing matrix 312. The mixing matrix 312comprises up to at least kN different multipath components of the atleast N different summations of the M source signals, and the mixingmatrix has a rank equal up to kN.

In particular, when CDMA waveforms propagate they often encountermultiple paths from the source to the destination. A rake receiver 316is specifically designed to capture a number of these individualinstances and combine them for a more robust signal decoding. While theoriginal signal propagates along each path, its properties are modifiedby the unique characteristics of the path. In some circumstances, themodification to the correlation and/or statistical properties of thereceived signal will be large enough so that they can be treated asseparable signal streams. A modified rake receiver 316 could be used toextract each modified stream and feed it as a unique entry into themixing matrix 312. While this means of increasing the rank will notalways be available, it will tend to be available in high multipathenvironments when it is most likely needed.

While a rake receiver 316 can exploit the different paths, the moregeneral approach applicable to any modulation technique is beam forming,as discussed in reference to FIG. 13. This differs from the rakereceiver 316 since beam forming is used for desired signal enhancementas well as desired signal rejection. The difference however is that therejected signal may actually be another version of the signal intendedfor the receiver. However, the receiver assembly 308 needs to detect anumber of these unique propagation path versions of the same signal inorder to build the mixing matrix 312 to a sufficient rank.

The third section of the roadmap addresses signal splitting for furtherpopulating the mixing matrix A. In one approach, the summation signalsare split using spreading codes. In another approach, the summationsignals are split using in-phase (I) and quadrature (Q) modules.

Signal splitting using spreading codes will now be discussed inreference to FIG. 14. The illustrated communications device 400comprises an antenna array 402 comprising N antenna elements 404 forreceiving at least N different summations of the M source signals. Acode despreader 406 is connected to the N antenna elements 404 fordecoding the at least N different summations of the M source signals.Each one of the N different summations includes k codes for providing kdifferent summations of the M source signals associated therewith.

A receiver assembly 408 is connected to the code despreader 406 forreceiving at least kN different summations of the M source signals. Ablind signal separation processor 410 is connected to the receiverassembly 408 for forming a mixing matrix 412 comprising the at least kNdifferent summations of the M source signals. The mixing matrix 412 hasa rank equal up to kN. The blind signal separation processor 410separates desired source signals 414 from the mixing matrix 412.

Depending on the modulation of the received signals, the above describedsignal splitting may be used for increasing the rank of the mixingmatrix A without increasing the number N of antenna elements. CDMAIS-95, CDMA2000 and WCDMA are examples of spread spectrum communicationssystems in which spreading codes are used. A common thread is that aunique code is processed with each signal to spread the data over alarger frequency band.

The same spreading code is processed with the received signal sum(desired signal, undesired signals and unknown noise sources). Thiscauses the desired signal to be reconstructed back to its originalfrequency bandwidth, while the interferers are spread over the widefrequency band.

The above listed CDMA implementations actually have many signal streamssimultaneously using the same frequency band. Each signal stream uses acode that is ideally orthogonal to all the others. If this condition ismet at the decoder, it means that only the signal of interest will bedespread. If the code of the Kth signal of the sum is used fordispreading, the resultant received signal sum x_(k) will be mostly madeup of an increased amplitude s_(k) term and either unchanged or lowervalued k−1 terms.

There often is some correlation between the CDMA signals, so theinterfering signals are somewhat reconstructed along with the desiredsignal. This is often due to the delay experienced by the individualsignals, and also the multipath occurrences of the signals. Some of theundesired signals, especially the CDMA ones, will increase in value. Theincrease will not be as significant as for the desired signal, but itwill still increase the overall noise value, and therefore decrease thesignal-to-noise ratio.

The form of the despread signals equation and the signals themselvesmeet the criteria for blind signal separation processing. In fact, ifone of the dispreading codes is individually applied for each knownsignal received by the communications device 400, individual summationsthat meet the ICA model requirements are obtained.

Therefore, there are as many row entries available for the mixing matrixas known codes, assuming of course, that they each produce linearlyindependent significant value. Under the right circumstances this willallow an increase of the mixing matrix to a value greater than thenumber of codes. For example, N antenna elements and M codes may provideNM matrix rows.

For illustrative purposes, 3 codes are assumed known and the 3 knowncode signals retain their orthogonality. In the code despreader 406, themixing matrix A has top 3 rows and bottom 3 rows each due to an antennastream after each stream has been despread by the 3 known codes. The offdiagonal 0 values are due to the orthogonality of the codes. The columnentries 4, 5 and 6 are for the general case of unknown signals of thesame index.

$\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4} \\x_{5} \\x_{6}\end{bmatrix} = {\begin{bmatrix}a_{11} & 0 & 0 & a_{14} & a_{15} & a_{16} \\0 & a_{22} & 0 & a_{24} & a_{25} & a_{26} \\0 & 0 & a_{33} & a_{34} & a_{35} & a_{36} \\a_{41} & 0 & 0 & a_{44} & a_{45} & a_{46} \\0 & a_{52} & 0 & a_{54} & a_{55} & a_{56} \\0 & 0 & a_{63} & a_{64} & a_{56} & a_{66}\end{bmatrix}\begin{bmatrix}s_{1} \\s_{2} \\s_{3} \\s_{4} \\s_{5} \\s_{6}\end{bmatrix}}$

The signals corresponding to the column entries 4, 5 and 6 can be otherpath versions of the known codes, or other cell signals of unknowncodes. Also, one signal may be Gaussian and the other signal is eitherCDMA signal groups obeying the central limit theorem so that they appearas a single Gaussian signal, e.g., release 4 channels. In other words, asufficient amount of non-random signals will add up to a Gaussiansignal. The interferers may be Non-Gaussian signal sources or at mostone Gaussian signal unknown to the network.

After despreading the known codes in the code despreader 406, the blindsignal separation processor 410 receives a mixing matrix 412 of rank 6.The rank of 6 is derived based upon 2 antenna elements multiplied by afactor of 3 since 3 codes are known.

The 6 signals are applied to the blind signal separation processor 410wherein the mixing matrix 412 having a rank of 6 is formed. The blindsignal separation processor 410 determines the separation matrix W fromonly the received signals modified by the channels: x=As. In theillustrated example, 6 signals are separable.

The blind signal separation processor 410 selects the signals to bedecoded. For example, the interferer signals may be dropped and allversions of the desired signals are selected. The selected signals areapplied to a demodulator module for demodulation. The demodulator useswell known equalization techniques that combine the multipath versionsof the same signal.

In the more general case the off diagonal values shown as 0 above forsimplicity, could actually be nonzero. This would be the more usual casewhen the correlation properties between the coded signals are notperfect. This would represent additional noise to each separated signal.However, as previously shown the rank of the matrix is sufficient toseparate these signals, so their value will be significantly reducedafter the blind signal separation processing. This leads to a decreasein noise, an increase in signal to noise ratio, and as indicated byShannon's law an increase in channel capacity.

Referring now to FIG. 15, the other approach for increasing the rank ofthe mixing matrix A without increasing the number N of antenna elementsis to separate a received mixed signal into its in-phase (I) andquadrature (Q) components. I and Q components of a coherent RF signalare components whose amplitudes are the same but whose phases areseparated by 90 degrees.

The communications device 500 comprises an antenna array 502 comprisingN antenna elements 504 for receiving at least N different summations ofthe M source signals. A respective in-phase and quadrature module 506 isdownstream to each antenna element 504 for separating each one of the Ndifferent summations of the M source signals received thereby into anin-phase and quadrature component set.

A receiver assembly 508 is downstream to each in-phase and quadraturemodule 506 for receiving the at least N in-phase and quadraturecomponent sets for the at least N different summations of the M sourcesignals. A blind signal separation processor 510 is downstream to thereceiver assembly 508 for forming a mixing matrix 512 comprising atleast 2N different summations of the M source signals. Each in-phase andquadrature component set provides 2 inputs into the mixing matrix 512.The mixing matrix 512 has a rank equal up to 2N, and the blind signalseparation processor 510 separates desired source signals 514 from themixing matrix 512.

One of the respective I and Q modules 506 downstream from an antennaelement 502 is illustrated in FIG. 16. A mixed signal received at theantenna element 502 is split by a pair of mixers 520. I and Q componentsare commonly produced by translating an intermediate frequency (IF)signal to another frequency range with two synchronous detectors towhich identical reference signals 90 degrees out of phase are applied.Together, the I and Q signals preserve the phase information containedin the IF signal, thereby enabling a signal having a positive frequencyto be differentiated from one having a negative frequency.

By separating the received mixed signals into I and Q components, thesize of the mixing matrix increases by a factor of 2. As long as the Iand Q components are encoded with different data streams, then the mixedsignal received at any antenna element may be split into two differentmixed signals.

In the case of differential encoding the nature of the modulation needsto be analyzed to determine if I and Q meet the linearity requirement.For instance, it has been shown for GSM that the GMSK encoding can beassumed linear when used with appropriate filtering, and processed inthe receiver as if it were BPSK encoding. Since BPSK meets therequirements for blind signal separation processing, the I and Q processdescribed can be used.

I and Q components can be used with any of the above described antennaarray embodiments to populate the mixing matrix A. When I and Q is used,the mixing matrix A can be populated as if 2 times the number of antennaelements were used. Another example could be the use of 2 antennaelements (a factor of 2) that are uncorrelated with unequal polarization(a factor of 2*2), and in combination with the I and Q components (afactor of 2*2*2) so that 8 independent mixed signal sums are generated.

This mechanism could also be used with the antenna array deflectiontechnique to create more sums of signals. Each of these sums could inturn also be separated into I and Q components.

Another aspect of the invention is directed to Multiple Input andMultiple Output (MIMO) antenna techniques for exploiting multiple use ofthe same RF channel. A receiver processing technique for interferencecancellation minimizes the number of antennas required by exploitingpattern diversity, rather than using antenna diversity to achieveincreased signaling robustness and corresponding data rates.

An antenna array has a changeable weighting in its receiver paths. Asthese weights are changed, the receive antenna pattern is modified. Byusing techniques similar to those well documented for blind signalseparation (BSS), a desired signal may be extracted from receiver datacontaining signals from a number of interferers.

Regardless of how the patterns are formed, the substitution of patterndiversity for antenna diversity in the receiving structure of MIMOimplementations is possible, as illustrated in FIG. 17. The number of Kpatterns ideally would be equivalent to the number of N antennaelements. However, the K patterns would be generated with L antennaelements which is lower than the N antenna elements required in theprior art. In a manner similar to the existing antenna array MIMOimplementations, M and K are equal only in the case where alltransmitted M spatial channels are discernable by the K receiverpatterns. Since this will generally be the case only for fixedtransmitter and receivers, an excess of receiver patterns or transmitterantennas will be necessary to achieve a minimum of K or M spatial gain.Multiuser detection processing techniques will be utilized to separateout the data channels in the receiver systems. All the methods discussedabove for building the mixing matrix may be used as part of thisimplementation.

Another aspect of the invention is directed to inter-symbol interference(ISI). Limitations when using Fourier transforms for reducing ISI areaddressed by the configuration provided in FIG. 18. The following blockshave been added on the transmit side to improve the Fourier transformmethod of reducing ISI: Viterbi encoding, repetition/puncturing andblock redundancy interleaving have been added to the transmit side. Onthe receive side, the following blocks have been added: BSS interferenceremoval, block de-interleaving, de-repetition/de-puncturing and Viterbidecoding.

The “Viterbi Encoding” has a robust redundancy that overcomesinaccuracies in the data decoding process. Alternate forms of codingsuch as turbo coding are also applicable. The “Repetition or Puncturing”enables data block matching between the source data rate and thetransmitted data rate. The “Block Interleaving” randomizes thesequentially arriving source data to maximize the probability of properdecoding, in that it improves resilience to propagation channelconditions. This introduces block errors due to, for example, a severefade, by distributing the block errors prior to the Viterbi decoderwhich can recover the data stream from randomly distributed errors muchmore effectively than block errors. The “BSS Interference Removal”reduces the signal to the intended signal prior to conversion back intothe time domain.

Given that the resulting frequency domain signal has a knownstatistically characteristic, which is unlikely to be uniform, the bestway to cope with the non-uniform distribution (level of the PAR) wouldbe to add in a non-linear mapper (to equalize the signal level acrossthe frequencies) at the output of the FFT, and a reverse transform atthe input to the IFFT.

In addition, this signal would typically be modulated and banded into atransmit frequency in a realistic scenario so adding in a modulator, upconverter and down converter, demodulator would complete the picture.There will be a discontinuity at the boundaries between the transmittedwaveforms. This can be mitigated in several ways. One would be to add aguard band between the waveforms in which a curve is interpolatedbetween the waveforms to minimize the frequency components generated.All the methods discussed above for building the mixing matrix may beused as part of this implementation.

Another aspect of the invention is directed to pattern diversity tosupport layer space communications. Referring now to FIG. 19, in thepreferred embodiment the transmitter changes the power levels for eachlayered space stream on a time slotted basis. The streams thereforearrive at the receiver with various power levels, which provide suitabledifferences in the received signals for population of a matrix suitablefor BSS separation processing. Since all the power adjustments are doneat the transmitter, the number of L antenna elements at the receiver isone, and no pattern generation hardware or software components areneeded at the receiver.

This approach also addresses the prior art in that small angulardifferences between arriving signals is no longer a problem in creatingpattern contours that adequately differ between the signals.

In another embodiment, there are significant interferers other than fromthe desired transmitter. If there is a single such interferer, thedifferences between it and the changing desired transmitter wave frontswill be adequate to have the BSS processing separate all the signals. Ifthere is more than one significant interferer the rank of the matrix maynot be adequate. The system performance could be improved by creatingadditional pattern changes at the receiver. While this is a deviationfrom the preferred embodiment, it still requires significantly fewerpatterns than before, and therefore, a less involved implementation atthe receiver.

In another embodiment, multiple streams of data are summed together fortransmission via one power amplifier via a single antenna element. On atime slotted basis the relative power level among the summed signals isvaried in a fashion suitable for BSS decoding at the receiver. Anadvantage of this approach is that the individual signal streams in thecomposite signal experience the identical propagation path effects,which means the relative signal relationships are maintained between thetransmitter and the receiver. This provides a very robust decodingsituation at the receiver.

This concept is scalable in that a number of individual sums of signalscan be sent via different antenna elements. Robust signal separation cantherefore be obtained along with multipath diversity gains and/orspatial capacity gains. To address the issue of peak to average signalpower ratios ideally being constant, the powers of the summed signalscould be adjusted in a fashion that maintains a near constant powerlevel. All the methods discussed above for building the mixing matrixmay be used as part of this implementation.

Another aspect of the invention is directed to undulating patterns tosupport multiple simultaneous transmitters. Referring now to FIG. 20,multiple devices transmitting to the access point modulate their RFpatterns. The intended access point and unintended access points willtherefore receive different power level versions of the transmittedsignals. This provides the information necessary for BSS to separate thesignals.

The modulation can be as simple as changing the transmitted power. Thiscan be done independent of the pattern's contour, so omni-directional,sectored, or even beam formed patterns can be used. Other techniquessuch as changing the bore sight of a transmission beam can also be used.

The most effective approach is to have the transmitters use aligned timeslots. The timing can be set by using internal clocks in the devices, orsyncing up to a common time mark sent by the access point. If there ismisalignment as to when the signals arrived at the receiver, there is adegradation in the BSS ability to separate the signals. Alignment can beadjusted by determining the distances to the devices, or measuring thetime delay. Timing advance or retardation techniques can then be used bythe accessing devices.

Given that the signal received gain changes are both being used by BSSequipped access points which consider them targets and in other casesinterferers, the proper receiver to align with may vary. If there is nooverall network coordination, the intended receiver should be alignedto. If there is overall network coordination, measurements may show thatthe best approach is to make the signal easier to remove as aninterferer, while still providing adequate alignment for separation atthe intended receiver.

If there are other signal sources which do not use the RF power levelmodulation technique, classical signal rejection techniques can be used.Alternately, the receiver may use patterns or other means to increasethe rank of the BSS suitable matrix. Even if the latter means areutilized, the degree of the matrix information derived will greatlyreduce the overhead to implemented at the access point receiver. All themethods discussed above for building the mixing matrix may be used aspart of this implementation.

Another aspect of the invention is directed to adjusting BSS RF decodingfor optimized processing and power drain. The number of signals thatneed to be separated to decode the stream(s) of interest are reduced. Ingeneral the rank of the decoding matrix determines the number of themost significant signals that will be separated, while the rest of thesignals are treated as noise. This value therefore needs to be at aminimum inclusive of the signals to be decoded. A possibly higherminimum may be necessary to decrease the noise component so that thesignal to noise ratio allows an acceptable decoding error rate.

FIG. 21 illustrates implementation of the receiver only operation. FIG.22 is a superset of FIG. 21 and also includes data from thetransmitter(s) to the receiver, and optionally, data from the receiverto the transmitter(s).

If the options to fill the matrix exceed the rank necessary foroperation, the antenna array control can reduce the number of optionsbeing utilized. Some selections from the available set may be moredesirable than others, and the optimum selection can allow for a lowermatrix rank. This set can be determined by examination of the signalsfrom the various options in comparison with the other options, by trialand error techniques (e.g., comparisons of results with option k usedand not used), or by historical tracking of conditions and results.Which method or combination of methods used can also be determined basedon effectiveness given known conditions and historical evidence.

When a device is known to be within range of significant signals fromseveral sources, as occurs in coverage overlap regions, the highestpower signals can be expected to come from significantly differentdirections. The options should therefore be chosen to providesignificant signal differences in those directions.

With respect to encoding, the error correcting encoding determines theerror rates that can be tolerated in the raw decoded streams. Since theraw error rate is also a function of the subset of the matrix filloptions, there is a tradeoff between these settings. A feedback andcontrol loop between the encoder and decoder can be used to choose theoptimum mutual settings.

If the receiver is found not to be in a power limited situation (e.g.,power by line voltage), the decoder may increase its matrix rank. Thiscan be used for several purposes. A higher rank may reduce the noise,which increases the signal to noise ratio, which in turn reduces theerror rate. Reduced noise may be used to increase the transmit datarate, reduce the error correction encoding, or improve the overallreliability of the link.

Shifting the burden of matrix filling to the receiver can also reducethe load on the transmitters, which can be exploited if there is acontrol loop between the two. Conversely, a device using a battery maytry to negotiate an increase in rank creation to the more robustlysupplied device(s).

By changing timing settings, the most robust operation requires that thedecoding matrix be recalculated for every symbol. Often however, thecoherence time exceeds the number of symbols, such that measurements areonly needed at a rate slightly faster than the coherence time. Reducingthe decoding matrix determination occurrences will save power andprocessor overhead.

Monitoring the changes in the matrix from one occurrence to another isused to determine how often the decoding matrix must be recalculated. Inwide band systems the subchannels often have individual coherence times.Each subchannel can have its own decoding matrix and associatedmeasurement rate. This eliminates the need to recalculate one very largedecoding matrix at the fastest necessary rate. In general, the sum ofmeasurements for the sub-decoding matrixes will be less than for the useof one large one.

With respect to pattern transmission, if the source is creatingpatterns, the receiver can adjust its matrix fill receive options toprovide adequate matrix rank. The receiver can base its value oninformation as to the transmission characteristics it is informed of bythe transmitter(s), measurements on the received streams and decodeddata, or negotiated settings with the source(s). In the negotiated casethe resource constraints of the source may also be taken into account,so that it is possible that either one could assume a higher burden inorder to offload the other the one.

With respect to matrix solving techniques, in general the decodingmatrix will not vary much from one calculation to the next. The priorvalues can therefore be used as seeds to iterative determination of thesolution, which will be less processor intense than determination fromscratch. When the matrix is large to be begin with, iterative decodingwill usually be faster even when the solution is determined from anunknown state. This is a well know way to solve large ranked, fairlyfull matrices.

In general, combinations of all of the above are possible depending onavailable components, revision code levels, suitable equipment, andother factors which affect plausible operation. All the methodsdiscussed above for building the mixing matrix may be used as part ofthis implementation.

Another aspect of the invention is directed to undulating patterns tosupport effective area coverage. With respect to pattern transmission,the basic concept is to use sectored coverage patterns at theinfrastructure sites. The actual number of sectors utilized varies withcapacity needs and related cost factors. Real implementations may varyfrom a single sector, to an arbitrarily large number. The sectorsthemselves may be subdivided in the azimuth or elevation or azimuth andelevation planes. A key benefit of using sectoring is that it alleviatesthe need for tracking the device at the other end of the link as per thebeam forming method. Leaving the coverage region of one sector foranother is therefore reduced to a classical handoff situation.

The prior art has the receiver generating the pattern changes suitablefor BSS signal separation processing. In contrast, the transmitterutilizes techniques so that a suitable BSS decoder environment at leastpartially exists. In some implementations this will mean the receiverneed not generate any undulating patterns. In other implementations, itmeans the number of undulating patterns is significantly reduced.

One embodiment is for one transmission point. This embodiment addressesthe situation when it is unknown whether other transmission sources inthe region are also operating. Referring to FIG. 23, the transmitpattern contours are undulated in a timing sequencing know to thereceiver.

The changes in the transmit pattern are timed to coincide with divisionsof the transmit symbol. Instead of bore sight movement, the contour ofthe pattern is changed and held constant for each time slot. Thecoverage area therefore does not significantly change, and there is noforesight tracking issue to contend with.

The receiver will experience a change in wave front power level due tothe changing transmission contours. The BSS matrix will therefore bepopulated with the differences of the various signal streams atdifferent relative gain values.

If the received dominant signals are all from one or more transmittersusing the undulating signaling, the receiver merely takes samples duringeach pattern change, and uses the resulting data to populate the matrixfor BSS signal separation.

If there is a mix of transmitters using the undulating signaling andothers are not using it, the receiver can use classical signalseparation techniques to account for them. Methods such as beam formingand multi-user detection may be used, for instance. However, the BSSmethod will usually be more robust. When practical, the receiver canimplement pattern deformation and generate enough additional patterns toincrease the rank of the BSS matrix above the number of signals to beseparated.

For the BSS decoder implementation for example, if three contours withthree signals are sent by the transmitter and there are two othersignals being received, the receiver would need to generate at least twocontours to separate the interferers against each other. This is threecontours less than would have been needed if the transmitter were notgenerating its own set, so the implementation burden on the receiver isalways reduced.

If a transmitter is sending a single stream along a signal path, thepattern contour set need not be rotational or dissimilar. This isbecause the signal as detected at the receiver is being changed relativeall other received signals. The transmitter may therefore use a simplepower change for the overall pattern rather than needing to change theshape of the contour. If only one other stream is summed at thereceiver, BSS will be able to separate them even though one is constantin amplitude. This is because the power dithering source provides thechanges necessary for its operation. If more than one other stream isreceived, they appear as a single grouped interferer to BSS, unless thereceiver itself uses other separation means, or has its own undulatingpattern generation capability.

A pattern transmitter in the receive mode will now be discussed. SinceBSS processing of multiple pattern contours is an excellent method forsignal separation, the same techniques used to generate the transmitpatterns can also be used to generate multiple receiver values. The onlycost factor for BSS reception when transmission is already supported, istherefore the BSS processing overhead.

User equipment receiver feedback to the transmitter will now bediscussed. While not strictly necessary, feed back information from theuser equipment receiver can be used to improve the overall operation ofthe links. For instance, the receiver can determine the degree to whicheach change in pattern contour provides useful data. This information isfed back to the transmitter. The transmitter can then adjust itsoperation to improve the link, utilize less power, or cause lessinterference to other communication links. Some of the adjustments couldbe: which and in what sequence each pattern is used, and how manychanges are made during the course of a symbol transmission (i.e.,change from M to N contours). Adjustments in contour changes per symbolwill need to be conveyed to the receiver for best performance.

A second embodiment involves multiple transmission points that are knownto be using the above described approach. The receiver operation for themulti-transmitter site implementation is basically the same as for thesingle site. The difference is that the patterns generated by eachtransmitter can be counted at the receiver for BSS signal separation.

More robust operation however may be obtained by receiving informationfrom the network as to the nature of the coordinated transmissionparameters. For instance, the rank of the matrix, which in turn dictatesthe number of required patterns, can be adjusted. The receiver'sgeneration of patterns, when available, is therefore adjusted per thisinformation. Network wide radio resource management can utilizeinformation fed back the user equipment to establish network widepattern usage, orientations, power levels and timing. All the methodsdiscussed above for building the mixing matrix may be used as part ofthis implementation.

Another aspect of the invention is directed to BSS and patternundulation to aid CDMA signal separation. For an BSS algorithm toeffectively separate the signals, the x_(i) receive signal must be anaggregate of the signals received at the antenna with relativelydifferent weighting factors associated with each individual signal. Thiscan be done at the transmitter, the receiver, or both positions. Whetherthe weighting factors are changed at the transmission end or thereception end, they can be changed per chip or set of contiguous chips.The basic requirement is that the aggregate signal be adjusted persymbol at least as many times as there are signals to separate.

FIG. 24 shows a case where in frequency the symbol is varied 12 times(12 chips). The parameter being varied is held constant for 4 chips.Three variations per symbol implies that three distinct signals can beseparated from the aggregate received signal.

If a transmitter is sending a single stream along a signal path, thepattern contour set need not be rotational or dissimilar. This isbecause the signal as detected at the receiver is being changed relativeall other received signals. The transmitter may therefore use a simplepower change for the overall pattern rather than needing to change theshape of the contour. If only one other stream is summed at thereceiver, BSS will be able to separate them even though one is constantin amplitude. This is because the power dithering source provides thechanges necessary for its operation. If more than one other stream isreceived, they appear as a single grouped interferer to BSS, unless thereceiver itself uses other separation means, or has its own undulatingpattern generation capability.

While not strictly necessary, feed back information from the userequipment receiver can be used to improve the overall operation of thelinks. For instance, the receiver can determine the degree to which eachchange in pattern contour provides useful data. This information is fedback to the transmitter. The transmitter can then adjust its operationto improve the link, utilize less power, or cause less interference toother communication links. While there are many ways of changing thepower profiles, some of the adjustments could be which and in whatsequence each pattern is used; how many changes are made during thecourse of a symbol transmission; and how to modulate or dither the powerto an individual link. Adjustments in contour changes per symbol willneed to be conveyed to the receiver for best performance.

Practical power amplifiers are best utilized in their linear operationalrange. With a large peak to average power ratio, the operational rangefor linear operation is reduced resulting in a reduced linear dynamiccontrol range for the PA, and hence a reduced operational distancebetween transmitter and receiver. When power is the transmit parameterbeing utilized, this concern can be mitigated by several approaches.

These approaches include when more than one sink is being powered by thesame amplifier, the BSS changes can be synchronized in a fashion suchthat the sum of the powers of all signals remains constant. In otherwords the increase of some transmissions is offset by the decrease ofothers. If the power is modulated at a value close to the chip rate, theexcess power can often be absorbed by the decoupling storage elementswith minor ripple induced. Excess power can diverted to a dissipationload.

The patterns in two or three dimensions may be created by a number ofmeans for both the transmit and the receive antennas, includingadjustment of the delay and power level of phase array antennas;parasitic antenna elements with switchable loads; changes inpolarization; changes in power plane loading which cause deflection ofthe patterns; mechanical movement of elements or reflectors; and acombination of any of the above. All the methods discussed above forbuilding the mixing matrix may be used as part of this implementation.

Another aspect of the invention is directed to a single receiver formultiple spatial independent channels. Switched parasitic antennas canbe coupled with a high speed digitizer and down converter to providemultiple spatial independent channels to a base band processingstructure. Multiple spatial independent channels are provided by using asingle low noise amplifier (LNA), a mixer, a local oscillator (LO), alow pass filter (LPF) and an analog-to-digital converter (ADC).

The multiple spatial independent channels obtained with this techniquemay be processed any of a variety of ways. Examples might includecoherent combining, blind signal separation (BSS) or multiple inputmultiple output (MIMO) receive processing.

The system principles are described below and relate to FIG. 25. Thepreferred embodiment consists of a single antenna array with switchingcomponents into inductors and capacitors. The band pass filter limitsboth the frequency band and total RF power presented to the LNA. The LNAis not just a low noise amplifier for the received signal. The mixer andLO tune the RF signal down to either an intermediate frequency (IF) orto base band DC. Either implementation is compatible with the back endprocessing.

The antenna switching, optional LO switching and demultiplexor switchingare all driven by the same digital sequence generator so that the Nchannels of signal are produced from the N diversity modes of theantenna. This produces a single channel RF output from the mixer topresent to the LPF and ADC.

The ADC, while not shown in the figure as such, is synchronous to thesame digital sequence generator that drives the antenna modes, optionalLO and demultiplexor. Considering a signal with carrier frequency Fc andmodulation bandwidth B, the demiltiplexor acts as a down-samplingoperation with impulses for the pulse shape. For an array with Nelements, the sampling frequency of the ADC must be at least 2*N*B. TheN is needed since only one of every N samples will be presented to ademodulator chain in the base band processor. The 2*B is needed tosatisfy the Nyquist sampling theory. Therefore, the signal bandwidthreceived by this system is also limited by the switching speed of thedevice.

The demultiplexor alternates samples to each of the N paralleldemodulator circuits inside the BBP. The sample distribution scheme mustnot be in groups but instead, sequential distribution. For example, ifthere are three antenna diversity options (left, right and omni) thenN=3. The samples from the ADC numbered 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12 would be distributed as such 1, 4, 7, 10 to the first demodulatorchain; 2, 5, 8, 11 to the second demodulator chain; and 3, 6, 9, 12 tothe third demodulator chain.

As mentioned before, the demodulators could be a form of coherentcombining, BSS or either of the two common MIMO demodulation techniques.This could be N instantiations of a single demodulation circuit or onepackage that expects N spatially independent channels. The coherentcombining could be the weighting of soft decisions or manipulations ofhard decisions. Some implementation limitations are discussed below.They include signal to noise ratio (SNR) considerations, noise figure,impedance matching, and received signal power.

If you assume that the antenna array has a bandwidth that is matched tothe received signal, the in-band SNR has remained the same. However, thein-band signal energy has been reduced by a factor of N² compared tothat of a conventional array.

Since the LNA is the first effective component in the signal path afterthe antenna array, the noise figure is not as much a concern as whenswitched arrays start with a PIN diode. Since each channel after thedemultiplexor receives 1/N of the signal power, the LNA gain requirementis increased by 10 log₁₀N to retain comparable signal amplitudes at theoutput of the mixer.

Switching among different antenna elements will introduce a change inimpedance matching characteristics. This is not the case for the antennaimplementation which always has the “active” antenna element as the onlyone directly connected to the RF path. The other “parasitic” antennaelements are only influential on the RF path.

An alternate embodiment that could be compatible with some MIMO andother parallel path transmission schemes is to integrate tuning the LOto different carrier frequencies as well as switching to differentdiversity modes of the antenna array. This could be done synchronous orindependent of each other. In time they must still occur simultaneous,but the state of each (array mode versus carrier frequency) does notneed to stay in phase.

This would be a useful implementation to receive the 802.11g+ waveformswhere two regular 802.11g waveforms are transmitted on differentcarriers in parallel. In this case, you would alternate between theupper and lower carrier frequency on the LO and then in a differentpattern, alternate the different diversity modes of the antenna array.

The mixer can be set to down-convert the RF waveform to an IF or tobaseband DC. This changes some of the sampling requirements of the ADC.Intentional aliasing and other techniques can perform IF under samplingand still recover the information content intended.

This approach also considers the dual use of the antenna for bothreceive and transmit functions. For some applications such as satellitereception, the transmit function is not required. For time divisionduplexed systems (such as WLAN, WiMAX, WCDMA-TDD, TD-SCDMA, etc.) ortime slotted FDD systems (such as GSM/GPRS) where receive and transmitare not simultaneous, the receive antenna can be multiplexed when thetransmit mode can be considered independent. For full duplex FDD systems(such as CDMA2000 or WCDMA-FDD) the transmit function may beaccomplished by way of a separate antenna(s). Any of these airinterfaces may use any of the enabled demodulator techniques (coherentcombining, BSS, MIMO).

Another aspect of the invention is directed to BSS as applied to CDMAreceiver processing. Antenna arrays with adequate separation betweenantenna elements are suitable for feeding the decoding chains. A surveyof the available literature indicates that in general this is the beliefof those skilled in the art.

Other documents discuss what is referred to as Single AntennaInterference Cancellation (SAIC) techniques. Those that utilize BSS,require that the modulation have correlated and or statisticallyindependent I and Q channels to create a rank 2 matrix. These decoderstherefore separate one interferer and the desired signal. If there aretwo interferers, existing SAIC techniques are not viable. They refer tothis as using a “virtual” second antenna.

The prior art can be improved upon by obtaining independent sums of thesignals by the existing art means, and by other methods not presentlyexploited in the literature. While I and Q means are practical in someradio access networks, they may not be suitable for CDMA encoding. Allthe methods discussed above for building the mixing matrix may be usedas part of this implementation.

While these techniques increase the rank of the ICA usable matrix andmake it more likely the application of the ICA will also extract thedesired signals, it cannot be guaranteed. So the techniques justdetailed still need to be used to select the appropriate decoding chain.For instance, you would need to back off from ICA processing if it wasoverly detrimental to the signal sum being processed.

In a second embodiment, a different decoding chain is utilized asillustrated in FIG. 26. At Node A an example of a signal set is shown inFIG. 27. A single interferer is shown for clarity, but the samearguments can be applied to multiple interferers and an increased matrixrank. The noise floor is exceeded by a narrow band interferer, and thedesired CDMA signal is below the noise floor.

At node B in FIG. 28, the interferer has been extracted. The “selector”determines if the extracted signals are indeed interferers. If nointerferers are present, no signal is selected. If a signal has thecharacteristics of the desired signal, it is not selected. If one ormore interferers are selected, they are presented to the “inverter”(Node C). ICA extraction can invert or not invert a received signal, anda determination is necessary as to whether each signal needs to beinverted to match the received signal.

The interferers, with the correct amplitude sign, are presented to thenegative input of the summer at Node D. One skilled in the art would ofcourse recognize that alternative, but equivalent implementations arepossible. For instance a pure summer could be utilized at this stage,and the inverter would only be employed when the signals were extractedwith the non-inverted waveform. A delayed version of the originalreceived signal (Node A) is presented at the other summer input. Thedelay value is equal to the delays incurred by the ICS, Select, and“inverter” processing. One skilled in the art would of course recognizethat alternative, but equivalent implementations are possible. Forinstance, the delay and summer functional blocks could be replaced by aminimization block that shifts and sums the two signals until a minimumis realized.

At Node D in FIG. 29, the interferers have been removed. At Node E inFIG. 30, the Rake receiver has de-spread the signal, which now may bepresented to the base band decoder. A further detail of this embodimentis that the signals gathered by the antenna structure can be obtainedvia the options per the previously discussed embodiment for enhancingthe existing art.

It should be recognized the structure as shown in FIG. 26 is only oneway to implement the outlined invention. Rather than having the“selector” present no signal when appropriate, the prior artimplementation of selecting a different path other the other either inpre or post processing position could also be used. The tradeoffs haveto do with processing delays, cost of implementation, robustness ofoverall operation, and to some degree designer's choice. Only theunderlying fundamental concept of subtracting the interferers from thesignal stream before presentation to the rake receiver needs to beretained in all variations to be of the same invention.

While the prior explanation is shown for a perfect removal ofinterferers, it should be realized that not all interferers may beremoved. The removal of any interferers however will in general providefor improved performance over the prior art, given that the Rake decoderwill be dealing with an improved signal set.

The CDMA signal by its nature is more Gaussian than its despreadversion, and will tend to be more difficult for ICA to detect. Theremoval of some data associated with the desired signal however is alsopossible, since the signal still retains some statistical significance.Once again the removal of the interferers will usually be much moresignificant, and an overall gain in what is presented to the Rakedecoder. Alternately, the overall decoding process could be furtherenhanced by using an incremental approach to the process. Meaning thesignals could be examined in more detail as to inclusion or exclusion,and/or the number of signals removed can be incrementally increased ordecreased and the integrity of the decoded signal measured for degree ofimprovement or worsening of the results.

A key point of this embodiment is that ICA is used on signals it canlikely identify, and is not used on the CDMA signals prior to the Rakeprocessing, during which it would be difficult to identify and/orextract.

Another aspect of the invention is directed to hybrid minimum meansquared error matrix-pencil separation weights for blind signalseparation via patterns. Reference is again directed to U.S. Pat. No.6,931,362 in which multiple sensors are required to provide linearlyindependent summations signals. The '362 patent is incorporated hereinby reference. The above described antenna arrays may be used instead ofthe multiple sensors, yet the post-processing as disclosed in the '362patent is still applicable.

Many modifications and other embodiments of the invention will come tothe mind of one skilled in the art having the benefit of the teachingspresented in the foregoing descriptions and the associated drawings. Inaddition, other features relating to blind signal separation aredisclosed in copending patent applications filed concurrently herewithand assigned to the assignee of the present invention and are entitledBLIND SIGNAL SEPARATION USING CORRELATED ANTENNA ELEMENTS, Ser. No.11/232,500; BLIND SIGNAL SEPARATION USING POLARIZED ANTENNA ELEMENTS,Ser. No. 11/233,329; BLIND SIGNAL SEPARATION USING ARRAY DEFLECTION,Ser. No. 11/233,160; BLIND SIGNAL SEPARATION USING SIGNAL PATHSELECTION, application Ser. No. 11/233,316; BLIND SIGNAL SEPARATIONUSING SPREADING CODES, application Ser. No. 11/232,610; and BLIND SIGNALSEPARATION USING I AND Q COMPONENTS, application Ser. No. 11/233,307,the entire disclosures of which are incorporated herein in theirentirety by reference. Therefore, it is to be understood that theinvention is not to be limited to the specific embodiments disclosed,and that modifications and embodiments are intended to be includedwithin the scope of the appended claims.

1. A communications device for separating source signals provided by Msignal sources, the communications device comprising: an antenna arraycomprising N antenna elements for receiving at least N differentsummations of the M source signals, with N and M being greater than 1,said N antenna elements comprising at least one antenna element forreceiving at least one of the N different summations of the M sourcesignals, and at least two correlated antenna elements for receiving atleast two of the N different summations of the M source signals; said atleast two correlated antenna elements being uncorrelated with said atleast one antenna element; a receiver connected to said antenna arrayfor receiving the at least N different summations of the M sourcesignals; and a blind signal separation processor connected to saidreceiver for forming a mixing matrix comprising the at least N differentsummations of the M source signals, the mixing matrix having a rankequal up to at least N, said blind signal separation processor forseparating desired source signals from the mixing matrix.
 2. Acommunications device according to claim 1 wherein N=M.
 3. Acommunications device according to claim 1 wherein the rank of themixing matrix is K, where K<N, and said blind signal separationprocessor separating K of the M source signals from the mixing matrix.4. A communications device according to claim 1 wherein N>M.
 5. Acommunications device according to claim 1 wherein said at least twocorrelated antenna elements have different polarizations.
 6. Acommunications device according to claim 5 wherein the differentpolarizations are orthogonal to one another.
 7. A communications deviceaccording to claim 1 wherein said at least two antenna elementscomprises 3 antenna elements that are also correlated and have differentpolarizations so that tri-polarization is supported for receiving 3different summations of the M source signals.
 8. A communications deviceaccording to claim 7 wherein said at least two correlated antennaelements have different polarizations.
 9. A communications deviceaccording to claim 1 wherein said at least one antenna element alsocomprises at least two correlated antenna elements for receiving atleast two of the N different summations of the M source signals.
 10. Acommunications device according to claim 1 wherein said at least twocorrelated antenna elements comprise at least two active antennaelements for forming a phased array.
 11. A communications deviceaccording to claim 1 wherein said at least two correlated antennaelements comprise at least one active antenna element and at least onepassive antenna element for forming a switched beam antenna.
 12. Acommunications device according to claim 1 wherein said antenna arrayforms at least N antenna beams for receiving the at least N differentsummations of the M source signals, each antenna beam having 3 db pointsdown from a maximum gain point thereof providing for signal rejection inat least one direction of an approaching signal.
 13. A communicationsdevice according to claim 1 wherein said antenna array forms at leastone antenna pattern for receiving at least one of the N differentsummations of the M source signals, the at least one antenna patternhaving substantially no 3 db points down from a maximum gain pointthereof resulting in no signal rejection in any direction of anapproaching signal.
 14. A communications device according to claim 1wherein each summation of the M source signals is linear.
 15. Acommunications device according to claim 1 wherein said blind signalseparation processor separates the desired source signals from themixing matrix based on principal component analysis (PCA).
 16. Acommunications device according to claim 1 wherein said blind signalseparation processor separates the desired source signals from themixing matrix based on independent component analysis (ICA).
 17. Acommunications device according to claim 1 wherein said blind signalseparation processor separates the desired source signals from themixing matrix based on single value decomposition (SVD).
 18. A methodfor operating a communications device for separating source signalsprovided by M signal sources, the communications device comprising anantenna array, a receiver connected to the antenna array, and a blindsignal separation processor connected to the receiver, the methodcomprising: receiving at the antenna array at least N differentsummations of the M source signals, the N antenna elements comprising atleast one antenna element for receiving at least one of the N differentsummations of the M source signals, and at least two correlated antennaelements for receiving at least two of the N different summations of theM source signals; the at least two correlated antenna elements beinguncorrelated with the at least one antenna element; providing the atleast N different summations of the M source signals to the receiver;and processing by the blind signal separation processor the at least Ndifferent summations of the M source signals received by the receiver,the processing comprising forming a mixing matrix comprising the atleast N different summations of the M source signals, the mixing matrixhaving a rank equal up to at least N, and separating desired sourcesignals from the mixing matrix.
 19. A method according to claim 18wherein N=M.
 20. A method according to claim 18 wherein the at least twocorrelated antenna elements have different polarizations.
 21. A methodaccording to claim 20 wherein the different polarizations are orthogonalto one another.
 22. A method according to claim 18 wherein the at leasttwo antenna elements comprises 3 antenna elements that are alsocorrelated and have different polarizations so that tri-polarization issupported for receiving 3 different summations of the M source signals.23. A method according to claim 22 wherein the at least two correlatedantenna elements have different polarizations.
 24. A method according toclaim 18 wherein the at least one antenna element also comprises atleast two correlated antenna elements for receiving at least two of theN different summations of the M source signals.
 25. A method accordingto claim 18 wherein the at least two correlated antenna elementscomprise at least two active antenna elements for forming a phasedarray.
 26. A method according to claim 18 wherein the at least twocorrelated antenna elements comprise an active antenna element and atleast one passive antenna element for forming a switched beam antenna.27. A method according to claim 18 wherein the antenna array forms atleast N antenna beams for receiving the at least N different summationsof the M source signals, each antenna beam having 3 db points down froma maximum gain point thereof providing for signal rejection in at leastone direction of an approaching signal.
 28. A method according to claim18 wherein the antenna array forms at least one antenna pattern forreceiving at least one of the N different summations of the M sourcesignals, the at least one antenna pattern having substantially no 3 dbpoints down from a maximum gain point thereof resulting in no signalrejection in any direction of an approaching signal.
 29. A methodaccording to claim 18 wherein each summation of the M source signals islinear.
 30. A method according to claim 18 wherein the blind signalseparation processor separates the desired source signals from themixing matrix based on principal component analysis (PCA).
 31. A methodaccording to claim 18 wherein the blind signal separation processorseparates the desired source signals from the mixing matrix based onindependent component analysis (ICA).
 32. A method according to claim 18wherein the blind signal separation processor separates the desiredsource signals from the mixing matrix based on single valuedecomposition (SVD).